Average transaction size is the average amount of money that each customer spends with your company.
Average transaction size is a great metric to track because it gives you a sense of how much your customers are spending with your company.
Average transaction size is also a great metric to track because it gives you a sense of how much your customers are spending with your company.
If you have a high average transaction size, it means that your customers are spending a lot of money with your company. If you have a low average transaction size, it means that your customers are spending a lot of money with your company.
It can be difficult to calculate Average Transaction Size directly inside of Redshift; that's where Causal comes in.
Causal is a modelling tool which lets you build models on top of your Redshift data. You simply connect Causal to your Redshift account, and then you can build formulae in Causal to calculate your Average Transaction Size.
Causal lets you build models effortlessly and share them with interactive, visual dashboards that everyone will understand.
In Causal, you build your models out of variables, which you can then link together in simple plain-English formulae to calculate metrics like Average Transaction Size. This makes your models easy to understand and quick to build, so you can spend minutes, not days, on your models.
When you're done, you can share the link to your model with stakeholders. They'll be able to view your model's outputs in a visual dashboard, rather than a jumble of tabs and complex formulae. The dashboards are interactive, letting viewers tweak your assumptions to see how they affect the model's outputs.
Causal lets you add visuals in a single click, letting you plot out graphs and distributions for metrics like Average Transaction Size.